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At least 1,261 records · Page 70

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NASA NTRS1998

Image enhancement by non-linear extrapolation in frequency space

An input image is enhanced to include spatial frequency components having frequencies higher than those in an input image. To this end, an edge map is generated from the input image using a high band pass filtering technique. An enhancing map is subsequently generated from the edge map, with the enhanced map having spatial frequencies exceeding an initial maximum spatial frequency of the input image. The enhanced map is generated by applying a non-linear operator to the edge map in a manner which preserves the phase transitions of the edges of the input image. The enhanced map is added to the input image to achieve a resulting image having spatial frequencies greater than those in the input image. Simplicity of computations and ease of implementation allow for image sharpening after enlargement and for real-time applications such as videophones, advanced definition television, zooming, and restoration of old motion pictures.

Anderson, Charles H.↗

NASA NTRS2001

Magnetically coupled signal isolator

A current determiner having an output at which representations of input currents are provided having an input conductor for the input current and a current sensor supported on a substrate electrically isolated from one another but with the sensor positioned in the magnetic fields arising about the input conductor due to any input currents. The sensor extends along the substrate in a direction primarily perpendicular to the extent of the input conductor and is formed of at least a pair of thin-film ferromagnetic layers separated by a non-magnetic conductive layer. The sensor can be electrically connected to electronic circuitry formed in the substrate including a nonlinearity adaptation circuit to provide representations of the input currents of increased accuracy despite nonlinearities in the current sensor, and can include further current sensors in bridge circuits.

Black, Jr., William C.↗

NASA NTRS2007

Method and apparatus for loss of control inhibitor systems

Active and adaptive systems and methods to prevent loss of control incidents by providing tactile feedback to a vehicle operator are disclosed. According to the present invention, an operator gives a control input to an inceptor. An inceptor sensor measures an inceptor input value of the control input. The inceptor input is used as an input to a Steady-State Inceptor Input/Effector Output Model that models the vehicle control system design. A desired effector output from the inceptor input is generated from the model. The desired effector output is compared to an actual effector output to get a distortion metric. A feedback force is generated as a function of the distortion metric. The feedback force is used as an input to a feedback force generator which generates a loss of control inhibitor system (LOCIS) force back to the inceptor. The LOCIS force is felt by the operator through the inceptor.

A'Harrah, Ralph C.↗

NASA NTRS2007

Method and apparatus for loss of control inhibitor systems

A'Harrah, Ralph C.↗

NASA NTRS2010

Project Management Using Modern Guidance, Navigation and Control Theory

The idea of control theory and its application to project management is not new, however literature on the topic and real-world applications is not as readily available and comprehensive in how all the principals of Guidance, Navigation and Control (GN&C) apply. This paper will address how the fundamental principals of modern GN&C Theory have been applied to NASA's Constellation Space Suit project and the results in the ability to manage the project within cost, schedule and budget. A s with physical systems, projects can be modeled and managed with the same guiding principles of GN&C as if it were a complex vehicle, system or software with time-varying processes, at times non-linear responses, multiple data inputs of varying accuracy and a range of operating points. With such systems the classic approach could be applied to small and well-defined projects; however with larger, multi-year projects involving multiple organizational structures, external influences and a multitude of diverse resources, then modern control theory is required to model and control the project. The fundamental principals of G N&C stated that a system is comprised of these basic core concepts: State, Behavior, Control system, Navigation system, Guidance and Planning Logic, Feedback systems. The state of a system is a definition of the aspects of the dynamics of the system that can change, such as position, velocity, acceleration, coordinate-based attitude, temperature, etc. The behavior of the system is more of what changes are possible rather than what can change, which is captured in the state of the system. The behavior of a system is captured in the system modeling and if properly done, will aid in accurate system performance prediction in the future. The Control system understands the state and behavior of the system and feedback systems to adjust the control inputs into the system. The Navigation system takes the multiple data inputs and based upon a priori knowledge of the input, will develop a statistical-based weighting of the input to determine where the system currently is located. Guidance and Planning logic of the system with the understanding of where it is (provided by the navigation system) will in turn determine where it needs to be and how to get there. Lastly, the system Feedback system is the right arm of the control system to allow it to affect change in the overall system and therefore it is critical to not only correctly identify the system feedback inputs but also the system response to the feedback inputs. And with any systems project it is critical that the objective of the system be clearly defined for not only planning but to be used to measure performance and to aid in the guidance of the system or project.

Hill, Terry↗

NASA NTRS2006

Multichannel Phase and Power Detector

An electronic signal-processing system determines the phases of input signals arriving in multiple channels, relative to the phase of a reference signal with which the input signals are known to be coherent in both phase and frequency. The system also gives an estimate of the power levels of the input signals. A prototype of the system has four input channels that handle signals at a frequency of 9.5 MHz, but the basic principles of design and operation are extensible to other signal frequencies and greater numbers of channels. The prototype system consists mostly of three parts: An analog-to-digital-converter (ADC) board, which coherently digitizes the input signals in synchronism with the reference signal and performs some simple processing; A digital signal processor (DSP) in the form of a field-programmable gate array (FPGA) board, which performs most of the phase- and power-measurement computations on the digital samples generated by the ADC board; and A carrier board, which allows a personal computer to retrieve the phase and power data. The DSP contains four independent phase-only tracking loops, each of which tracks the phase of one of the preprocessed input signals relative to that of the reference signal (see figure). The phase values computed by these loops are averaged over intervals, the length of which is chosen to obtain output from the DSP at a desired rate. In addition, a simple sum of squares is computed for each channel as an estimate of the power of the signal in that channel. The relative phases and the power level estimates computed by the DSP could be used for diverse purposes in different settings. For example, if the input signals come from different elements of a phased-array antenna, the phases could be used as indications of the direction of arrival of a received signal and/or as feedback for electronic or mechanical beam steering. The power levels could be used as feedback for automatic gain control in preprocessing of incoming signals. For another example, the system could be used to measure the phases and power levels of outputs of multiple power amplifiers to enable adjustment of the amplifiers for optimal power combining.

Li, Samuel↗

NASA NTRS2012

A Computational Methodology for Simulating Thermal Loss Testing of the Advanced Stirling Convertor

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two highefficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. In an effort to improve net heat input predictions, numerous tasks have been performed which provided a more accurate value for net heat input into the ASCs, including the use of multidimensional numerical models. Validation test hardware has also been used to provide a direct comparison of numerical results and validate the multi-dimensional numerical models used to predict convertor net heat input and efficiency. These validation tests were designed to simulate the temperature profile of an operating Stirling convertor and resulted in a measured net heat input of 244.4 W. The methodology was applied to the multi-dimensional numerical model which resulted in a net heat input of 240.3 W. The computational methodology resulted in a value of net heat input that was 1.7 percent less than that measured during laboratory testing. The resulting computational methodology and results are discussed.

Reid, Terry V.↗

NASA NTRS2020

Investigation of a Helicopter Individual Blade Control (IBC) System in Two Full-Scale Wind Tunnel Tests: Volume I

This report presents the data acquired during the testing of an individual blade control (IBC) system on a full-scale helicopter rotor in two test entries in the NASA Ames 40- by 80-Foot Wind Tunnel. The objective of these investigations was to evaluate the potential benefits of using IBC to improve rotor performance, reduce blade vortex interaction (BVI) noise, and alleviate helicopter vibrations. The wind tunnel tests were an international, collaborative effort between NASA, the U.S. Army Aeroflightdynamics Directorate, ZF Luftfahrttechnik GmbH, Eurocopter Deutschland GmbH, and the German Aerospace Laboratory (DLR). They were conducted as a task of the U.S./German Memorandum of Understanding (MOU) on Helicopter Aeromechanics. The IBC tests were performed using a full-scale BO-105 helicopter rotor mounted to the NASA/U.S. Army Rotor Test Apparatus (RTA). The first test, performed in 1993, was the first full-scale wind tunnel test to explore the effects of an IBC system on rotor vibration, noise, and performance. In this test, the pitch links of the rotor were replaced by servo-actuators. The servo-actuators and IBC control system were designed and manufactured by ZF Luftfahrttechnik GmbH. This control system allowed the pitch of each rotor blade to be changed independently of the other blades. The IBC inputs had large effects on the hub vibrations and BVI noise. However, the rotor hub moments were not retrimmed with each new IBC input. This resulted in an out-of-trim rotor configuration. The same IBC system was used in the second IBC test performed in 1994. This test more carefully investigated the potential of IBC to simultaneously reduce noise and vibration and also investigated the effect of IBC on rotor performance in high-speed-cruise flight. In the 1994 test, the hub moment and rotor thrust were readjusted to maintain rotor trim as the IBC inputs were applied. For this reason, the data taken from the second test are considered to be more accurate, except for some unique IBC input combinations not repeated in the second test. IBC controls that were evaluated were single-frequency inputs from 2/rev to 6/rev and multi-harmonic combinations of these frequencies to form pulses, wavelets, and doublets. Extensive data were acquired for each IBC data point. These data included rotor performance, average and time-varying hub loads, rotor blade bending loads, control system loads, inboard and outboard blade pitch motions, and BVI noise data. The rotor balance hub force and moment data included the mean values, half-peak-to-peak values, and sine/cosine harmonics up to the 20th rotor harmonic. The time history and averaged Fourier spectrum for each measurement are available electronically from NASA Ames Research Center. The data indicate that significant reduction in both BVI noise and hub vibration can be obtained using IBC. The 2/rev input produced the best single-frequency results. At a typical descent flight condition, 2/rev IBC combined with other IBC harmonics reduced the BVI noise up to 12 dB (85 percent) at some microphone locations. At the same time, this input could also reduce the dominant 4/rev vibratory hub loads by up to 75 percent. The data also show that performance improvements of up to 7 percent were obtained using 2/rev IBC at high-speed forward flight conditions. An analysis of the hydraulic power requirements for BVI noise suppression, vibration reduction, and rotor performance improvement is included in this report. This analysis shows that the power required by the IBC system is negligible at low-speed flight conditions, and that a net gain of 3 percent of rotor horsepower can be achieved at high-speed flight conditions.

Investigation↗

DOE OSTI2021

Dimming LED circuit augmenting DC/DC controller integrated circuit

Embodiments include systems, methods, and apparatuses for providing a dimming function in a single stage AC input light emitting diode (LED) driver with a controller that contains an on-chip error amplifier and an on-chip fixed reference voltage source coupled to a first input of the error amplifier. The controller controls a duty cycle of a switching transistor to cause a feedback voltage, applied to a first package input terminal, to match the reference voltage. To achieve a dimming function, a voltage across a current sense resistor in series with the LEDs is applied to a first input of a high gain differential amplifier, and a variable dimming control voltage is applied to a second input of the differential amplifier. The output of the differential amplifier is coupled to the first package input terminal. The differential amplifier input signals will be matched at the target LED current level.

Song, Zhengrong↗

DOE OSTI2022

Analog vector-matrix multiplication by capacitive elements with resistive state storage

An array circuit includes a plurality of vector-matrix multiplication (VMM) elements arranged in rows and columns. The VMM elements are configured to collectively perform multiplication of an input vector by a programmed input matrix to generate a plurality of output values that are representative of a result matrix that is the result of multiplication of the input vector and the input matrix. The VMM elements store states of the input matrix. Input voltages to the array are representative of elements of the input vector. A VMM element draws charge from a column read line based upon charging of a capacitor in the VMM. An integrator circuit connected to the column read line outputs a voltage that is indicative of a total charge drawn from the column read line by elements connected to the read line, which voltage is further indicative of an element of a result matrix.

Agarwal, Sapan↗

DOE OSTI2021

Physics-Informed Machine Learning Models for Predicting the Progress of Reactive-Mixing

This paper presents a physics-informed machine learning (ML) framework to construct reduced-order models (ROMs) for reactive-transport quantities of interest (QoIs) based on high-fidelity numerical simu-lations. QoIs include species decay, product yield, and degree of mixing. The ROMs for QoIs are applied to quantify and understand how the chemical species evolve over time. First, high-resolution datasets for constructing ROMs are generated by solving anisotropic reaction-di?usion equations using a non-negative finite element formulation for di?erent input parameters. The reactive-mixing model input parameters are: time-scale associated with flipping of velocity, spatial-scale controlling small/large vortex structures of velocity, perturbation parameter of the vortex-based velocity, anisotropic dispersion strength/contrast, and molecular diffusion. Second, random forests, F-test, and mutual information criterion are used to evaluate the importance of model inputs/features with respect to QoIs. We observed that anisotropic dispersion strength/contrast is the most important feature and time-scale associated with flipping of velocity is the least important feature. Third, Support Vector Machines (SVM) and Support Vector Regression (SVR) are used to construct ROMs based on the model inputs. The constructed SVR-ROMs are then used to predict scaling of QoIs. We also present estimates and inequalities on the QoIs, which inform that the species decay, mix, and produce in an exponential fashion. These inequalities also inform that a radial basis function is the most suitable kernel for the SVM/SVR models for QoIs. It is observed that R2-score for SVR-ROMs on unseen data is greater than 0.9, implying that the SVR-ROMs are able to predict the reaction-diffusion system state reasonably well. Finally, in terms of the computational cost, the proposed SVM-ROMs are O(107) times faster than running a high-fidelity finite element simulation for evaluating QoIs. This makes the proposed ML-based ROMs attractive for reactive-transport sensing and real-time monitoring applications as they are significantly faster yet reasonably accurate.

Mudunuru, Maruti K.↗

DOE OSTI2023

Neural network-based control of an ultrafast laser

With the recent advances in machine learning (ML) and data science (DS), the control, modeling, and analysis of these complex systems continues to improve. In this work, we report on the optimization of the intensity of a femtosecond laser using feedforward neural networks (FFNN) that model the input–output relationships of the data. The input parameters of the system were optimized to achieve the required performance of the femtosecond laser. We propose a neural network-based control system to model the relationship between the spectral amplitude and phase of the input laser pulse at the amplifier input and the shape of the output pulse. Low-jitter laser parameter inputs and the resulting laser pulse duration were modeled, and the resulting correlation between the input and output data was used to optimize the laser pulse. Here, we demonstrate improved processing and laser control performance.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Sensitivity and uncertainty of the IFR-1 BISON benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered for adoption by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This paper summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment.For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. Here, the resulting variations in benchmark predictions were normalized to calculate sensitivities. These sensitivities were then used to inform input selections for the UQ.The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of the benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because the confidence intervals associated with benchmark predictions were wide. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

An efficient method to identify uncertainties of WRF-Solar variables in forecasting solar irradiance using a tangent linear sensitivity analysis

Uncertainty in predicting solar energy resources introduces major challenges in power system management and necessitates the development of reliable probabilistic solar forecasts. As the first part of the development of probabilistic forecasts based on the Weather Research and Forecasting model with solar extensions (WRF-Solar), this study presents a tangent linear approach to identify input variables responsible for the largest uncertainties in predicting surface solar irradiance and clouds. A tangent linear analysis is capable of efficiently investigating sensitivities of output variables with respect to various input variables of WRF-Solar because this approach avoids the computational burden of perturbing the initial conditions of individual input variables. We develop tangent linear models (TLMs) for six WRF-Solar physics packages that control the formation and dissipation of clouds and solar radiation, and we evaluate the validity of TLMs using a linearity test. The tangent linear sensitivity analysis is conducted under various scenarios based on satellite observations and model simulations to consider realistic input conditions. A simple method is used to quantify the impact of the uncertainty of input variables on the output variables from the TLMs. The results demonstrate that uncertainties in the output variables that are the focus of this study—including global horizontal irradiance, direct normal irradiance, cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes—are highly sensitive to uncertainties in 14 input variables. This study indicates that the tangent linear method can identify key variables of physics modules in WRF-Solar that can be stochastically perturbed to generate ensemble-based probabilistic forecasts.

14 SOLAR ENERGY↗

DOE OSTI2023

Universal linear intensity transformations using spatially incoherent diffractive processors

Abstract Under spatially coherent light, a diffractive optical network composed of structured surfaces can be designed to perform any arbitrary complex-valued linear transformation between its input and output fields-of-view (FOVs) if the total number ( N ) of optimizable phase-only diffractive features is ≥~2 N i N o , where N i and N o refer to the number of useful pixels at the input and the output FOVs, respectively. Here we report the design of a spatially incoherent diffractive optical processor that can approximate any arbitrary linear transformation in time-averaged intensity between its input and output FOVs. Under spatially incoherent monochromatic light, the spatially varying intensity point spread function ( H ) of a diffractive network, corresponding to a given, arbitrarily-selected linear intensity transformation, can be written as H ( m , n ; m ′, n ′) = | h ( m , n ; m ′, n ′)| 2 , where h is the spatially coherent point spread function of the same diffractive network, and ( m , n ) and ( m ′, n ′) define the coordinates of the output and input FOVs, respectively. Using numerical simulations and deep learning, supervised through examples of input-output profiles, we demonstrate that a spatially incoherent diffractive network can be trained to all-optically perform any arbitrary linear intensity transformation between its input and output if N ≥ ~2 N i N o . We also report the design of spatially incoherent diffractive networks for linear processing of intensity information at multiple illumination wavelengths, operating simultaneously. Finally, we numerically demonstrate a diffractive network design that performs all-optical classification of handwritten digits under spatially incoherent illumination, achieving a test accuracy of >95%. Spatially incoherent diffractive networks will be broadly useful for designing all-optical visual processors that can work under natural light.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Measurement of the branching fraction of D s + → ℓ + ν ℓ via e + e − → D s * + D s * −

Based on 10.64 fb − 1 of e + e − collision data taken at center-of-mass energies between 4.237 and 4.699 GeV with the BESIII detector, we study the leptonic D s + decays using the e + e − → D s * + D s * − process. The branching fractions of D s + → ℓ + ν ℓ ( ℓ = μ , τ ) are measured to be B D s + → μ + ν μ = ( 0.547 ± 0.02 6 stat ± 0.01 6 syst ) % and B D s + → τ + ν τ = ( 5.60 ± 0.1 6 stat ± 0.2 0 syst ) % , respectively. The product of the decay constant and Cabibbo-Kobayashi-Maskawa matrix element | V c s | is determined to be f D s + | V c s | = ( 246.5 ± 5.9 stat ± 3.6 syst ± 0.5 input ) μ ν and f D s + | V c s | = ( 252.7 ± 3.6 stat ± 4.5 syst ± 0.6 input ) τ ν MeV , respectively. Taking the value of | V c s | from a global fit in the Standard Model, we obtain f D s + = ( 253.2 ± 6.0 stat ± 3.7 syst ± 0.6 input ) μ ν and f D s + = ( 259.6 ± 3.7 stat ± 4.6 syst ± 0.6 input ) τ ν MeV , respectively. Conversely, taking the value for f D s + from the latest lattice quantum chromodynamics calculation, we obtain | V c s | = ( 0.986 ± 0.02 3 stat ± 0.01 4 syst ± 0.00 3 input ) μ ν and | V c s | = ( 1.011 ± 0.01 4 stat ± 0.01 8 syst ± 0.00 3 input ) τ ν , respectively. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

DOE OSTI2023

A Modified Sequence-to-point HVAC Load Disaggregation Algorithm

This paper presents a modified sequence-to-point (S2P) algorithm for disaggregating the heat, ventilation, and air conditioning (HVAC) load from the total building electricity consumption. The original S2P model is convolutional neural network (CNN) based, which uses load profiles as inputs. We propose three modifications. First, the input convolution layer is changed from 1D to 2D so that normalized temperature profiles are also used inputs to the S2P model. Second, a drop-out layer is added to improve adaptability and generalizability so that the model trained in one area can be transferred to other geographical areas without labelled HVAC data. Third, a fine-tuning process is proposed for areas with a small amount of labelled HVAC data so that the pre-trained S2P model can be fine-tuned to achieve higher disaggregation accuracy (i.e., better transferability) in other areas. The model is first trained and tested using smart meter and sub-metered HVAC data collected in Austin, Texas. Then, the trained model is tested on two other areas: Boulder, Colorado and San Diego, California. Simulation results show that the proposed modified S2P algorithm outperforms the original S2P model and the support-vector machine based approach in accuracy, adaptability, and transferability.

Ye, Kai↗

DOE OSTI2022

Novel Quadratic High Gain Boost Converter With Adaptive Soft-Switching Scheme and Reduced Conduction Loss

In this article, an improved soft-switching quadratic boost converter is proposed. Instead of inserting an additional active clamp or auxiliary zero-voltage transition circuit at the switching node, the proposed topology connects the high-voltage switching node to the input diode node by replacing one of the input diodes with a low-rated switch. The proposed topology can attain soft-switching condition for all the switches and input diode turns- off under zero-current switching (ZCS). The operation of input-side switch not only aids zero-voltage switching (ZVS) turn- on for the main switch but also helps in reducing the conduction loss. Also, the input-side switch operates under ZCS turn- on and ZVS turn- off , making it a loss economical solution. An adaptive timing scheme for driving the input switch is proposed, which can ensure soft-switching condition under varying gain and load range. The detailed operational modes, analysis, and design considerations of the proposed topology are presented. A 250 W hardware prototype is built to validate the performance of the proposed converter operating at 100 kHz switching frequency. Results with adaptive soft-switching scheme shows that the converter is modulated to achieve its best efficiency condition under various system conditions. Furthermore, a peak efficiency of 96.1% at 155 W and efficiencies above 95.75% over a wide load range are achieved using all Si devices.

14 SOLAR ENERGY↗